WOLFRAM SYSTEMMODELER

InventoryForresterNormalNoise

Inventory simulation with random orders

Diagram

Wolfram Language

In[1]:=
SystemModel["SystemDynamics.IndustrialDynamics.Inventory.InventoryForresterNormalNoise"]
Out[1]:=

Information

Customer Demand Modeled as Noise

Customer demand usually fluctuates in a random fashion. Therefore, it is modeled in this simulation as normally distributed random noise with a mean value of mean=1000 and a standard deviation of stdev=100. The noise is sampled once per week and kept constant for the corresponding week. The order flow is modeled using the equation:

RRR(t) = RRRini + normal(1000,100);


Simulate the model across 10 years (520 weeks), and plot on a single graph the incoming orders, the production flow in the factory, and the levels of goods in retail, distribution, and the factory as functions of time:

Choose Radau-IIa as your integration algorithm. It handles noise input better than DASSL.


Parameters (3)

RRRiniTop

Value: 1000

Type: Real (¹/wk)

Description: Inital value of customer requests at retail

RRDiniTop

Value: RRRiniTop

Type: Real (¹/wk)

Description: Inital value of requisitions received at distribution

RRFiniTop

Value: RRRiniTop

Type: Real (¹/wk)

Description: Inital value of requisitions received at factory

Outputs (5)

randomNoise

Type: Real (¹/wk)

Description: Random noise signal

factoryFlow

Type: Real (¹/wk)

Description: Manufacturing flow at factory

retailStock

Type: Real

Description: Stock of goods in retail

distributionStock

Type: Real

Description: Stock of goods in distribution

factoryStock

Type: Real

Description: Stock of goods in factory

Components (4)

Factory1

Type: Factory

Distribution1

Type: Distribution

Retail1

Type: Retail

NoiseNormal1

Type: NoiseNormal